Survey of multipath routing protocols for mobile ad hoc networks

This survey investigates multipath routing protocols for mobile ad hoc networks (MANETs). The main objectives of multipath routing protocols are to provide reliable communication and to ensure load balancing as well as to improve quality of service (QoS) of MANETs. These multipath protocols are broadly classified into five categories based on their major goals. The goals are to improve delay, provide reliability, reduce overhead, maximize network life and support hybrid routing. Multipath routing protocols address issues such as multiple paths discovery and maintaining these paths. Issues, objectives, performances, advantages and disadvantages of these protocols are investigated and summarized. A checklist is provided as a guideline so that a network designer can choose an appropriate multipath routing protocol to meet the network's application objectives.     

Distributed Learning for Planning Under Uncertainty Problems with Heterogeneous Teams

This paper considers the problem of multiagent sequential decision making under uncertainty and incomplete knowledge of the state transition model. A distributed learning framework, where each agent learns an individual model and shares the results with the team, is proposed. The challenges associated with this approach include choosing the model representation for each agent and how to effectively share these representations under limited communication. A decentralized extension of the model learning scheme based on the Incremental Feature Dependency Discovery (Dec-iFDD) is presented to address the distributed learning problem. The representation selection problem is solved by leveraging iFDD’s property of adjusting the model complexity based on the observed data. The model sharing problem is addressed by having each agent rank the features of their representation based on the model reduction error and broadcast the most relevant features to their teammates. The algorithm is tested on the multi-agent block building and the persistent search and track missions. The results show that the proposed distributed learning scheme is particularly useful in heterogeneous learning setting, where each agent learns significantly different models. We show through large-scale planning under uncertainty simulations and flight experiments with state-dependent actuator and fuel-burn- rate uncertainty that our planning approach can outperform planners that do not account for heterogeneity between agents.     

Automatic recognition of vigilance state by using a wavelet-based artificial neural network

In this study, 5-s long sequences of full-spectrum electroencephalogram (EEG) recordings were used for classifying alert versus drowsy states in an arbitrary subject. EEG signals were obtained from 30 healthy subjects and the results were classified using a wavelet-based neural network. The wavelet-based neural network model, employing the multilayer perceptron (MLP), was used for the classification of EEG signals. A multilayer perceptron neural network (MLPNN) trained with the Levenberg–Marquardt algorithm was used to discriminate the alertness level of the subject. In order to determine the MLPNN inputs, spectral analysis of EEG signals was performed using the discrete wavelet transform (DWT) technique. The MLPNN was trained, cross-validated, and tested with training, cross-validation, and testing sets, respectively. The correct classification rate was 93.3% alert, 96.6% drowsy, and 90% sleep. The classification results showed that the MLPNN trained with the Levenberg–Marquardt algorithm was effective for discriminating the vigilance state of the subject.     

Effect of high temperature heat treatment on intergranular corrosion of AlMgSi(Cu) model alloy

Copper containing 6000-series aluminium alloys may become susceptible to intergranular corrosion (IGC) as a result of improper thermomechanical processing. Effect of cooling rate after solution heat treatment on the corrosion behaviour of a model AlMgSi(Cu) alloy of nominal composition (wt%) 0.6 Mg, 0.6 Si, 0.2 Fe, 0.2 Mn and 0.1 Cu was investigated. Slow cooling rates were simulated by isothermal treatment for predetermined times in lower temperature baths immediately after solution heat treatment. Treatment for 10-100 s at temperatures below 400 °C introduced susceptibility to IGC. Longer heat treatment at the same temperatures introduced susceptibility to pitting. A corrosion resistant time zone was found between the zones of IGC and pitting at temperatures lower than 350 °C. Quenching in water after solution heat treatment prevented IGC. IGC was related to microgalvanic coupling between the noble Q-phase (Al₄Mg₈Si₇Cu₂) grain boundary precipitates and the adjacent depleted zone. Pitting was attributed to coarse particles in the matrix. Possible mechanisms causing the corrosion resistant intermediate zone are discussed. The results indicate possible methods for obtaining increased corrosion resistance of similar alloys by proper thermal processing.     

Voronoi diagrams with barriers and on polyhedra for minimal path planning

Two generalizations of the Voronoi diagram in two dimensions (E²) are presented in this paper. The first allows impenetrable barriers that the shortest path must go around. The barriers are straight line segments that may be combined into polygons and even mazes. Each region of the diagram delimits a set of points that have not only the same closest existing point, but have the same topology of shortest path. The edges of this diagram, which has linear complexity in the number of input points and barrier lines, may be hyperbolic sections as well as straight lines. The second construction considers the Voronoi diagram on the surface of a convex polyhedron, given a set of fixed source points on it. Each face is partitioned into regions, such that the shortest path to any goal point in a given region from the closest fixed source point travels over the same sequence of faces to the same closest point.     

Antenatal fetal risk assessment by blood-flow velocity waveforms

The purpose of this article is to study a system for antepartum fetal evaluation. The task is to investigate the Doppler ultrasound measurements of the umbilical artery and the cerebral artery to relate the health status of a fetus by using discriminant functions of pattern recognition. The authors then analyze the individual effects of various blood-flow velocity waveforms using principal component analysis.     

Prediction of effect of volume fraction, compact pressure and milling time on properties of Al-Al2O3 MMCs using neural networks

An artificial neural network (ANN) model was developed to predict the effect of volume fraction, compact pressure and milling time on green density, sintered density and hardness of Al-Al₂O₃ metal matrix composites (MMCs). Al-Al₂O₃ powder mixtures with various reinforcement volume fractions of 5, 10, 15% Al₂O₃ and milling times (0 h to 7 h) were prepared by mechanical milling process and composite powders were compacted at various pressure (300, 500 and 700 MPa). The three input parameters in the proposed ANN were the volume fraction, compact pressure and duration of the milling process. Green density, sintered density and hardness of the composites were the outputs obtained from the proposed ANN. As a result of this study the ANN was found to be successful for predicting the green density, sintered density and hardness of Al-Al₂O₃ MMCs. The mean absolute percentage error for the predicted values didn’t exceed 5.53%. This model can be used for predicting Al-Al₂O₃ MMCs properties produced with different reinforcement volume fractions, compact pressures and milling times.     

Nonstandard set theories and information management

The merits of set theory as a foundational tool in mathematics stimulate its use in various areas of artificial intelligence, in particular intelligent information systems. In this paper, a study of various nonstandard treatments of set theory from this perspective is offered. Applications of these alternative set theories to information or knowledge management are surveyed.